Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 751 135 33 146 326 298 394 913 605 155 169 168 348 360 392 29 258 935 299 67
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] NA 67 146 258 135 751 326 168 NA 605 360 913 392 348 298 NA 29 299 935 169 394 155 33
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 3 1 4 1 5 4 2 2 3 5
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y"
[26] "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y"
[26] "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "x" "u" "o" "v" "y" "D" "S" "Y" "Q" "T"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 8 18
which( manyNumbersWithNA > 900 )
[1] 12 19
which( is.na( manyNumbersWithNA ) )
[1] 1 9 16
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 913 935
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 913 935
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 913 935
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "D" "S" "Y" "Q" "T"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "x" "u" "o" "v" "y"
manyNumbers %in% 300:600
[1] FALSE FALSE FALSE FALSE TRUE FALSE TRUE FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE FALSE FALSE
[18] FALSE FALSE FALSE
which( manyNumbers %in% 300:600 )
[1] 5 7 13 14 15
sum( manyNumbers %in% 300:600 )
[1] 5
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] NA "small" "small" "small" "small" "large" "small" "small" NA "large" "small" "large"
[13] "small" "small" "small" NA "small" "small" "large" "small" "small" "small" "small"
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "UNKNOWN" "small" "small" "small" "small" "large" "small" "small" "UNKNOWN" "large"
[11] "small" "large" "small" "small" "small" "UNKNOWN" "small" "small" "large" "small"
[21] "small" "small" "small"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] NA 0 0 0 0 751 0 0 NA 605 0 913 0 0 0 NA 0 0 935 0 0 0 0
unique( duplicatedNumbers )
[1] 3 1 4 5 2
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 3 1 4 5 2
duplicated( duplicatedNumbers )
[1] FALSE FALSE FALSE TRUE FALSE TRUE FALSE TRUE TRUE TRUE
which.max( manyNumbersWithNA )
[1] 19
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 935
which.min( manyNumbersWithNA )
[1] 17
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 29
range( manyNumbersWithNA, na.rm = TRUE )
[1] 29 935
manyNumbersWithNA
[1] NA 67 146 258 135 751 326 168 NA 605 360 913 392 348 298 NA 29 299 935 169 394 155 33
sort( manyNumbersWithNA )
[1] 29 33 67 135 146 155 168 169 258 298 299 326 348 360 392 394 605 751 913 935
sort( manyNumbersWithNA, na.last = TRUE )
[1] 29 33 67 135 146 155 168 169 258 298 299 326 348 360 392 394 605 751 913 935 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 935 913 751 605 394 392 360 348 326 299 298 258 169 168 155 146 135 67 33 29 NA NA NA
manyNumbersWithNA[1:5]
[1] NA 67 146 258 135
order( manyNumbersWithNA[1:5] )
[1] 2 5 3 4 1
rank( manyNumbersWithNA[1:5] )
[1] 5 1 3 4 2
sort( mixedLetters )
[1] "D" "o" "Q" "S" "T" "u" "v" "x" "y" "Y"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 7.0 1.5 7.0 7.0 10.0 7.0 4.0 7.0 3.0 1.5
rank( manyDuplicates, ties.method = "min" )
[1] 5 1 5 5 10 5 4 5 3 1
rank( manyDuplicates, ties.method = "random" )
[1] 7 1 6 9 10 8 4 5 3 2
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.00000000 -0.50000000 0.00000000 0.50000000 1.00000000 -0.10812308 -2.28714919 -0.04818282
[9] -0.35614287 0.99657785 -0.05962949 -1.10161884 -0.78380958 -1.57000720 -2.32641992
round( v, 0 )
[1] -1 0 0 0 1 0 -2 0 0 1 0 -1 -1 -2 -2
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 -0.1 -2.3 0.0 -0.4 1.0 -0.1 -1.1 -0.8 -1.6 -2.3
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 -0.11 -2.29 -0.05 -0.36 1.00 -0.06 -1.10 -0.78 -1.57 -2.33
floor( v )
[1] -1 -1 0 0 1 -1 -3 -1 -1 0 -1 -2 -1 -2 -3
ceiling( v )
[1] -1 0 0 1 1 0 -2 0 0 1 0 -1 0 -1 -2
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 × 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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